Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11E429860A096063F76B30BC9E6D8BF7FA292C45DC7C66D1191AD03BF8ED5F10A94B412 |
|
CONTENT
ssdeep
|
192:T0oF2j6FOjH6OHL5HXySn+nhTnCn+nl9nD/xNuESvVCr5BHGmjPEs:Crt2rJYs |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ecd33c0e5b2c5964 |
|
VISUAL
aHash
|
00ffffffff938381 |
|
VISUAL
dHash
|
a10d074345272627 |
|
VISUAL
wHash
|
00f7e7ffff010300 |
|
VISUAL
colorHash
|
076000000c0 |
|
VISUAL
cropResistant
|
8107074165272627,0000000000000000,8d262527243d7973,3f3fa72167131333,9d1e3c5b5e6c1b1f |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 4 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)